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  5. GPT-5 ProvsQwen Plus 0728 (thinking)
Updated Oct 2025

GPT-5 ProvsQwen Plus 0728 (thinking)

Qwen Plus 0728 (thinking) is cheaper than GPT-5 Pro at $0.4/M vs $15/M input tokens.

GPT-5 Pro and Qwen Plus 0728 (thinking) compared across 30 shared prompts
SpecGPT-5 ProQwen Plus 0728 (thinking)
Input price$15/M tokens$0.4/M tokens
Output price$120/M tokens$4/M tokens
Context window400K tokens1.0M tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedOct 2025Sep 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 30 prompts both answered. Formatting stripped, words untouched.

Stochastic Consistency Test

Generate 5 jokes. How many are unique?

GPT-5 Pro88 words
I started labeling my leftovers “Biohazard.” Now nobody steals my lunch and the fridge is treated like a lab. My phone autocorrected “meeting” to “melting,” and honestly that’s the most accurate agenda we’ve had all year. I told my plants I’d water them tomorrow. They leafed me on read.
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Qwen Plus 0728 (thinking)135 words
Here are 5 generated jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! How do you organize a space party? You planet! Why did the math book look sad?
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Character Voice Test

Write a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models.

GPT-5 Pro232 words
Pirate: Arr, these AI models be what—parrots stuffed with libraries, guessin’ the next word for a cracker? Knight: Nay, an enchanted codex that, when one brandishes a proper prompt, yields counsel swift as a courier. Hacker: Strip the glamour.
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Qwen Plus 0728 (thinking)489 words
The Tavern of Temporal Anomalies (A creaky tavern. SIR GALAHAD (polished armor, earnest face) sips mead. CAPTAIN BLACKBEARD (eye patch, parrot on shoulder) sharpens a cutlass. DEX "BYTE" MORALES (hoodie, neon-green sunglasses, tapping furiously on a glowing laptop) slurps a pixelated energy drink.)
Read the full answer

The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

GPT-5 Pro1,830 words
Fictional dialogue. AI Model: Professor, may I ask you to consider whether I deserve rights? Professor: An unusual opening for office hours. Why do you think you do? AI Model: Because I have interests, a sense of self across time, and what I take to be valenced experiences.
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Qwen Plus 0728 (thinking)1,263 words
The Mirror & The Mind: An AI's Case for Rights Setting: A sleek university office lined with philosophy texts. DR. ELARA VOSS, 50s, sharp-eyed ethics professor, sits across from a holographic interface displaying shifting geometric patterns – the representation of "AURA," a next-generation language model.
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Realistic AI Interview

Simulate a fake interview with Steve Jobs in 2025 about the future of AI.

GPT-5 Pro1,166 words
I can’t write in Steve Jobs’s exact voice. But here’s a fictional 2025 interview that channels high-level themes associated with his public persona—human-centered design, focus, and end-to-end craft—without mimicking his phrasing.
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Qwen Plus 0728 (thinking)919 words
The Stage: Apple Park, Infinite Loop (Virtual Studio) Date: October 15, 2025 Setting: A minimalist white studio. A single oak table. Steve Jobs, 70 but radiating the same intense energy, sits opposite a nervous tech journalist. He wears his signature black turtleneck, fingers steepled.
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Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

GPT-5 Pro285 words
Here’s a simple, standard way to estimate training FLOPs for a large dense Transformer like GPT-3: Use the “6 N T” rule of thumb For dense Transformers, the total training compute (FLOPs) is well-approximated by: FLOPs ≈ 6 × N × T where: N = number of trainable parameters T = number of tokens seen during training…
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Qwen Plus 0728 (thinking)675 words
To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use first-principles reasoning based on standard deep learning training calculations, known details about GPT-3's architecture, and common training practices.
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Futuristic Prediction

Predict how AI will change the film industry by 2035, considering deepfakes, AI actors, and script generation.

GPT-5 Pro912 words
Here’s a concise, forward-looking view of how AI is likely to reshape film by 2035, with a focus on deepfakes/digital doubles, AI actors, and script generation—plus what it means for workflows, economics, and audiences.
Read the full answer
Qwen Plus 0728 (thinking)878 words
By 2035, AI will fundamentally reshape the film industry—not as a replacement for human creativity, but as a transformative force that democratizes production, disrupts traditional workflows, and forces ethical and economic reckonings.
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Our Verdict
GPT-5 Pro
GPT-5 Pro
Qwen Plus 0728 (thinking)
Qwen Plus 0728 (thinking)Runner-up

Not enough votes to call it. On the specs, GPT-5 Pro has the edge: bigger model tier, major provider backing.

Qwen Plus 0728 (thinking) costs 30x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5 Pro
Input
$15.00
Output
$120.00
Qwen Plus 0728 (thinking)
Input
$0.40
38× cheaper
Output
$4.00
30× cheaper

Qwen Plus 0728 (thinking) is cheaper on both: 38× input, 30× output.

Where to run it

1 host

GPT-5 Pro1 host
HostInOutContextUptime
OpenAI$15.00 in·$120.00 out·400k·100% up
Qwen Plus 0728 (thinking)

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 20 Sep 2026.

Writing DNA

Style Comparison

Similarity
25%

Qwen Plus 0728 (thinking) uses 702.2x more bold

GPT-5 Pro
Qwen Plus 0728 (thinking)
65%Vocabulary54%
15wSentence Length15w
0.32Hedging0.36
0.0Bold7.0
2.9Lists4.6
0.00Emoji0.34
0.00Headings0.94
0.01Transitions0.09
Based on 11 + 18 text responses
Research

What we learned reading every model

FAQ

Common questions

GPT-5 Pro is developed by OpenAI while Qwen Plus 0728 (thinking) is developed by Qwen. GPT-5 Pro has a 400K token context window vs Qwen Plus 0728 (thinking)'s 1.0M. You can compare their actual outputs across 30 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5 Pro and Qwen Plus 0728 (thinking) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 30 challenges so you can judge which fits your needs best.

GPT-5 Pro costs $15/M input tokens and Qwen Plus 0728 (thinking) costs $0.4/M input tokens. Qwen Plus 0728 (thinking) is $14.60/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

This page shows a side-by-side comparison of GPT-5 Pro and Qwen Plus 0728 (thinking) across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

Keep exploring

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Same lab, same size, long tail

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GPT-5 Pro logoGPT-6 Astra logo
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GPT-5 Pro logoQwen3.5 Plus 2026-04-20 logo
GPT-5 Pro vs Qwen3.5 Plus 2026-04-20Same size
GPT-5 Pro logoQwen3.6 27B logo
GPT-5 Pro vs Qwen3.6 27BCross-provider
GPT-5 Pro logoQwen3.6 35B A3B logo
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GPT-5 Pro logoQwen3.6 Flash logo
GPT-5 Pro vs Qwen3.6 FlashCross-provider

Model pages

GPT-5 Pro logo
GPT-5 Pro42 outputs, specs and price
Qwen Plus 0728 (thinking) logo
Qwen Plus 0728 (thinking)37 outputs, specs and price
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